Question

In a Word document, write an essay (3 page minimum, and citing references) that compares the various kinds of data integrity and business rules at the relationship, table, and field levels, and explains why each one is important. Additionally, your essay should provide specific examples of how data integrity can be compromised, and how the lack of appropriate business rules can have a negative impact on the operations of an organization.

Answer 1

Data has been widely labelled as the new oil and the new black gold - parallels that describe the value of big data to our economy and business. However, the analogy only fits in limited situations. Data also becomes a truly valuable commodity only when the data is of high quality determined based on a range of qualitative and quantitaive variables. These variables or dimensions may encompass data accuracy, completness, consistency, timeliness, validaty and uniqueness. Similarly, the data also needs to maintain its integrity to facilitate decisions.

However, Data integrity is oftern used as a proxy term for Data Quality. For data-driven business organizations, the parameters and rules that define the quality and integrity of data present vastly different implications. Data quality referes to the characteristics that determine the reliability of information to serve an intended purpose including planning, decision making and operations. Data integrity refers to the characteristics that determine the reliability of the information in terms of its physical and logical validity.

Business rules always have to do with the conduct and decisions of people. Integrity constraints and system rules always have to do with the integrity of data. In contrast to Integrity constraints, not all business rules can be avoided. The reason is that some business rules have to do with the way people understand concepts and make decisions. You can misapply such rules, but you really cant violate them per se.

Data integrity can be compromised in variety of ways, making data integrity practices an essential component of effective enterprise security protocols. Data Integrity may be compromised through:

- Human error, whether malicious or unintentional

- Transfer errors, including alterations or data compromise during transfer from one device to another

- Bugs, viruses/malware, hacking, and other cyber threats

- Compromised hardware, such as a device or disk crash

- Physical compromise to devices

Since only some of these compromises may be adequately prevented through data security, the case for data backup and duplication becomes critical for ensuring data Integrity. Other Data integrity is best practices include input validation to preclude the entering of invalid data, error detection/data validation to indentify errors in data transmission, and security measures such as data loss prevention, access control, data encryption, and more.

Business rules are used every day to define entities, attributes, relationships and constraints. Usually though they are used for the organization that stores or uses data to be an explanation of a policy, procedure, or principle. The data can be considered significant only after business rules are defined, without them its just records, but to a business they are the characteristics that are defined and seen by the company. Business rules help employees focus on and implement the actions within the organizations environment. Some things to think about when creating business rules are to keep them simple, easy to understand, keep them board so that everyone can have a similar interpretation. To be considered true, business rules must be in writing and kept up to date.